class_docstr: Inception v3 model from
  `"Rethinking the Inception Architecture for Computer Vision"
  <http://arxiv.org/abs/1512.00567>`_ paper.
  
  Parameters
  ----------
  classes : int, default 1000
      Number of classification classes.
  norm_layer : object
      Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
      Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
  norm_kwargs : dict
      Additional `norm_layer` arguments, for example `num_devices=4`
      for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
class_docstr_tok: ["Inception","v3","model","from","`","``","Rethinking","the","Inception","Architecture","for","Computer","Vision","''","<","http",":","\/\/arxiv.org\/abs\/1512.00567",">","`","_","paper",".","Parameters","--","--","--","--","--","classes",":","int",",","default","1000","Number","of","classification","classes",".","norm_layer",":","object","Normalization","layer","used","(","default",":",":","class",":","`","mxnet.gluon.nn.BatchNorm","`",")","Can","be",":","class",":","`","mxnet.gluon.nn.BatchNorm","`","or",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`",".","norm_kwargs",":","dict","Additional","`","norm_layer","`","arguments",",","for","example","`","num_devices=4","`","for",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`","."]
code: def hybrid_forward(self, F, x):
      x = self.features(x)
      x = self.output(x)
      return x
  
file_path: gluon-cv/gluoncv/model_zoo/inception.py
imports: from mxnet.context import cpu
  from mxnet.gluon.block import HybridBlock
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from mxnet.gluon.contrib.nn import HybridConcurrent
label_desc: Use image node_id 2 for calling the Inception3 obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: x